Abstract
IntroductionAlthough ECG interpretation is an essential skill in clinical medicine, medical students and residents often lack ECG competence. Novel teaching methods are increasingly being implemented and investigated to improve ECG training. Computer-assisted instruction is one such method under investigation; however, its efficacy in achieving better ECG competence among medical students and residents remains uncertain.Methods and analysisThis article describes the protocol for a systematic review and meta-analysis that will compare the effectiveness of computer-assisted instruction with other teaching methods used for the ECG training of medical students and residents. Only studies with a comparative research design will be considered. Articles will be searched for in electronic databases (PubMed, Scopus, Web of Science, Academic Search Premier, CINAHL, PsycINFO, Education Resources Information Center, Africa-Wide Information and Teacher Reference Center). In addition, we will review citation indexes and conduct a grey literature search. Data extraction will be done on articles that met the predefined eligibility criteria. A descriptive analysis of the different teaching modalities will be provided and their educational impact will be assessed in terms of effect size and the modified version of Kirkpatrick framework for the evaluation of educational interventions. This systematic review aims to provide evidence as to whether computer-assisted instruction is an effective teaching modality for ECG training. It is hoped that the information garnered from this systematic review will assist in future curricular development and improve ECG training.Ethics and disseminationAs this research is a systematic review of published literature, ethical approval is not required. The results will be reported according to the Preferred Reporting Items for Systematic Review and Meta-Analysis statement and will be submitted to a peer-reviewed journal. The protocol and systematic review will be included in a PhD dissertation.PROSPERO registration numberCRD42017067054; Pre-results.
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